Emerging technologies such as predictive analytics and artificial intelligence are changing the way care is delivered. However, true innovation in healthcare does not just require the integration of new technologies but also calls for a change in the mentality of individual providers and executives.
Here Matt Hawkins, the CEO of the healthcare revenue cycle technology company Waystar, answers four questions about how emerging technologies are changing healthcare and what hospital leaders can do to help their organizations overcome barriers to innovation.
Question: How are emerging technologies such as predictive analytics, machine learning and AI transforming healthcare?
Matt Hawkins: When people think about new and emerging technologies in healthcare, they might first think of clinical applications — predicting adverse events, assisting doctors in medical determinations and so on. Those are exciting possibilities. But emerging technology, such as AI, has an immediate, practical and real application on the administrative side. Providers can leverage AI to get paid fuller, faster, and more effectively, which frees up resources for patient and community care.
For example, administrative processes like getting prior authorizations, checking claim status and appealing denials have historically been manual, labor-intensive and costly. With new and emerging technologies, healthcare organizations have an opportunity to streamline and optimize these tasks, saving significant resources that can be put towards higher-value work. What’s more, these intelligent technologies eliminate much of the human error that can result in lost time or misinformation.
Q: What are some specific challenges that emerging technologies can help overcome?
MH: There are many opportunities for providers to use AI and other intelligent technologies to optimize every step of revenue cycle management.
Predictive analytics can be used to model a patient's propensity-to-pay, which helps providers prioritize which accounts to work in which order, resulting in a higher rate of more significant paid bills. Healthcare organizations can also leverage predictive analytics to identify patients who qualify for financial assistance, which can be a boon to patients and help providers reduce bad debt.
Another huge area of opportunity for AI lies in automating prior authorizations. Prior authorizations, the process by which payers determine if they will cover a prescribed procedure or medication, are meant to help patients avoid unexpected medical costs. But the process today is largely manual and prone to error, resulting in $30 billion annual cost in wrongful denials, inefficiencies and clerical errors. With AI and machine learning, providers can automate this process, resulting in faster authorizations with less cost and fewer denials — and fewer surprise bills for patients.
AI can also give billing teams insight into which denials have the highest likelihood of being overturned. This is a meaningful change in the outdated approach of dollar descending or aged denial follow-up. Allowing staff to focus their efforts on the denials with the greatest potential yield will ensure hospitals are receiving every dollar possible in overturning denials. As this technology evolves, it’s likely that AI will soon be able to predict future denials with a high degree of accuracy — in many ways the holy grail for revenue cycle teams.
In the big picture, healthcare providers of all sizes continue to experience margin pressure and are having to achieve more with slimmer budgets and fewer staff resources. At the same time, improving quality of care and patient satisfaction remain paramount. It can seem like a catch-22. Emerging technologies can take much of the burden off of billing and revenue cycle teams, and in many cases may be the only realistic solution to bringing in more money in less time.
Q: What are some barriers hospitals and health systems experience when looking to implement these technologies? How can these organizations overcome these challenges?
MH: To begin with, many organizations simply aren’t aware of the opportunities and solutions that are available today. Secondly, even if they are aware, they have to walk the tightrope between costs and revenue, making the case for upfront investment for long-term gain.
The good news is that, once decision-makers see the projected — and proven — ROI for intelligent technologies, they understand how much they have to lose by not making this investment. Inherent in the phrase "emerging technologies" is the truth that predictive analytics, machine learning and AI are the future of healthcare, whether they're adopted by any individual organization ahead of the curve or after they've become ubiquitous.
A third concern is the fear that emerging technologies, and AI in particular, are meant to replace human intelligence and judgment. The reality is that AI augments and informs the still very necessary human knowledge base. By automating some of the more mundane tasks, emerging technologies allow health organizations to focus their staff resources on other priorities, such as more nuanced cases or over-arching strategic initiatives. AI analyzes and learns from data with speed and accuracy humans can’t match. But it will always be up to a human to make the call on next steps.
Lastly, IT teams are already occupied with other work. Selecting and implementing another technology can seem burdensome. The solution to this challenge is to choose a vendor that will take as much off your IT team as possible and to communicate that this technology will ultimately free up resources once implemented.
Q: What should providers look for when partnering with technology vendors?
MH: Providers should seek to work with a partner who is invested in both the excellence of their technology and in the provider's long-term success in using it. Look for companies that have skilled data scientists on staff who are available to work with a hospital or health system to ensure they're getting the most out of data analytics initiatives. It's also important to find a partner with the capacity to review a healthcare provider's current systems and identify techniques and benchmarks for putting their data to use for maximum effect.
Organizations should also look for technology partners with highly trained, in-house client support that can take the burden off of internal teams.
Even more important than the choice of any specific vendor is the cultivation of a healthcare environment that is primed for innovation, encourages and supports increased collaboration across clinical and financial teams, and effectively communicates the value these technologies can provide to staff members. Machine learning and predictive analytics should be viewed as technologies that can support employees and help refine where they should focus their attention, to ensure optimal financial performance and outcomes.
The most successful organizations will choose technology vendors who operate with an innovation-first mentality and who can serve as guides in this ever-evolving landscape.
Emerging technologies such as predictive analytics and artificial intelligence are changing the way care is delivered. However, true innovation in healthcare does not just require the integration of new technologies but also calls for a change in the mentality of individual providers and executives.
Here Matt Hawkins, the CEO of the healthcare revenue cycle technology company Waystar, answers four questions about how emerging technologies are changing healthcare and what hospital leaders can do to help their organizations overcome barriers to innovation.
Question: How are emerging technologies such as predictive analytics, machine learning and AI transforming healthcare?
Matt Hawkins: When people think about new and emerging technologies in healthcare, they might first think of clinical applications — predicting adverse events, assisting doctors in medical determinations and so on. Those are exciting possibilities. But emerging technology, such as AI, has an immediate, practical and real application on the administrative side. Providers can leverage AI to get paid fuller, faster, and more effectively, which frees up resources for patient and community care.
For example, administrative processes like getting prior authorizations, checking claim status and appealing denials have historically been manual, labor-intensive and costly. With new and emerging technologies, healthcare organizations have an opportunity to streamline and optimize these tasks, saving significant resources that can be put towards higher-value work. What’s more, these intelligent technologies eliminate much of the human error that can result in lost time or misinformation.
Q: What are some specific challenges that emerging technologies can help overcome?
MH: There are many opportunities for providers to use AI and other intelligent technologies to optimize every step of revenue cycle management.
Predictive analytics can be used to model a patient's propensity-to-pay, which helps providers prioritize which accounts to work in which order, resulting in a higher rate of more significant paid bills. Healthcare organizations can also leverage predictive analytics to identify patients who qualify for financial assistance, which can be a boon to patients and help providers reduce bad debt.
Another huge area of opportunity for AI lies in automating prior authorizations. Prior authorizations, the process by which payers determine if they will cover a prescribed procedure or medication, are meant to help patients avoid unexpected medical costs. But the process today is largely manual and prone to error, resulting in $30 billion annual cost in wrongful denials, inefficiencies and clerical errors. With AI and machine learning, providers can automate this process, resulting in faster authorizations with less cost and fewer denials — and fewer surprise bills for patients.
AI can also give billing teams insight into which denials have the highest likelihood of being overturned. This is a meaningful change in the outdated approach of dollar descending or aged denial follow-up. Allowing staff to focus their efforts on the denials with the greatest potential yield will ensure hospitals are receiving every dollar possible in overturning denials. As this technology evolves, it’s likely that AI will soon be able to predict future denials with a high degree of accuracy — in many ways the holy grail for revenue cycle teams.
In the big picture, healthcare providers of all sizes continue to experience margin pressure and are having to achieve more with slimmer budgets and fewer staff resources. At the same time, improving quality of care and patient satisfaction remain paramount. It can seem like a catch-22. Emerging technologies can take much of the burden off of billing and revenue cycle teams, and in many cases may be the only realistic solution to bringing in more money in less time.
Q: What are some barriers hospitals and health systems experience when looking to implement these technologies? How can these organizations overcome these challenges?
MH: To begin with, many organizations simply aren’t aware of the opportunities and solutions that are available today. Secondly, even if they are aware, they have to walk the tightrope between costs and revenue, making the case for upfront investment for long-term gain.
The good news is that, once decision-makers see the projected — and proven — ROI for intelligent technologies, they understand how much they have to lose by not making this investment. Inherent in the phrase "emerging technologies" is the truth that predictive analytics, machine learning and AI are the future of healthcare, whether they're adopted by any individual organization ahead of the curve or after they've become ubiquitous.
A third concern is the fear that emerging technologies, and AI in particular, are meant to replace human intelligence and judgment. The reality is that AI augments and informs the still very necessary human knowledge base. By automating some of the more mundane tasks, emerging technologies allow health organizations to focus their staff resources on other priorities, such as more nuanced cases or over-arching strategic initiatives. AI analyzes and learns from data with speed and accuracy humans can’t match. But it will always be up to a human to make the call on next steps.
Lastly, IT teams are already occupied with other work. Selecting and implementing another technology can seem burdensome. The solution to this challenge is to choose a vendor that will take as much off your IT team as possible and to communicate that this technology will ultimately free up resources once implemented.
Q: What should providers look for when partnering with technology vendors?
MH: Providers should seek to work with a partner who is invested in both the excellence of their technology and in the provider's long-term success in using it. Look for companies that have skilled data scientists on staff who are available to work with a hospital or health system to ensure they're getting the most out of data analytics initiatives. It's also important to find a partner with the capacity to review a healthcare provider's current systems and identify techniques and benchmarks for putting their data to use for maximum effect.
Organizations should also look for technology partners with highly trained, in-house client support that can take the burden off of internal teams.
Even more important than the choice of any specific vendor is the cultivation of a healthcare environment that is primed for innovation, encourages and supports increased collaboration across clinical and financial teams, and effectively communicates the value these technologies can provide to staff members. Machine learning and predictive analytics should be viewed as technologies that can support employees and help refine where they should focus their attention, to ensure optimal financial performance and outcomes.
The most successful organizations will choose technology vendors who operate with an innovation-first mentality and who can serve as guides in this ever-evolving landscape.